Edge computing and its multi-access edge compute (MEC) sub-component could finally be ready to hit center stage, fulfilling long-held promise for a technology and service platform set to benefit telecom service providers and hyperscalers.

A recent report from IDC predicts spending on edge computing will hit $228 billion this year, which is a 14% increase compared to 2023. That growth is expected to push overall spend to nearly $378 billion by 2028.

IDC’s numbers include enterprise and service provider spending on hardware, software, professional services, and provisioned services for edge solutions. The analyst firm also tags the edge as “technology-related actions outside of centralized data centers, serving as an intermediary between connected endpoints and the core IT environment.”

That connectivity position is becoming increasingly important in the wake of the growing push around artificial intelligence (AI) and generative AI (genAI).

“As the focus of AI shifts from training to inference, edge computing will be required to address the need for reduced latency and enhanced privacy,” Dave McCarthy, research VP for cloud and edge services at IDC, wrote. “This trend not only optimizes operation efficiencies but also fosters new business models that were previously not possible with centralized infrastructure. Distributing applications and data to edge locations enables faster decision-making with reduced network congestion.”

IDC’s edge enthusiasm was cautiously echoed by Technology Business Research (TBR), which estimates the enterprise edge market will grow at a nearly 20% compound annual growth rate (CAGR) over the next several years to surpass more than $90 billion in revenues by 2027. The firm expects professional and managed services to be the fastest segment growers at a more than 23% CAGR, with software growing at just under 20% CAGR.

TBR did add that the broader tightening of IT spend is reining in investments, but the “deceleration of growth in the edge market will not be as severe as in other markets due to the strategic nature of edge investments.”

Who will benefit from edge investments? TBR also stated that hyperscalers were set to benefit from the edge opportunities, specifically citing efforts like Google’s air-gapped Distributed Cloud push and Amazon Web Services’ (AWS) Local Zones.

“With their vast access to data, the hyperscalers will be a natural choice for customers that do not want to move their genAI solutions to a separate compute ecosystem but want to process the data closer to the point of use,” TBR added.

Communication service providers are also angling for that edge opportunity.

Carriers have for years been touting the edge and MEC opportunity, including vocal support from Verizon CEO Hans Vestberg, who has admitted that his enthusiasm has been a step ahead of reality.

Vestberg during a recent investor conference noted that while the market itself continues to gain momentum, it could still be some time before market dynamics shine on true edge infrastructure.

“The loads are coming,” Vestberg said during the Goldman Sachs Communacopia + Technology Conference. “Probably it's going to take some time because the majority of genAI today is large language models that you're training, so they send them way back to the data centers. But as soon as they start doing, like Verizon, it's an application that you use, then you want it closer to the customer because of transport costs, security, [and] in certain cases, latency.”

Vestberg also boasted of Verizon’s long-standing partnerships with all three of the nation’s largest hyperscalers to boost its edge posture.

“We have processing, compute, storage, power already built across the nation with our mobile edge compute, so I think that no one in the telco world is better prepared than Verizon to be part of the genAI edge compute of the time,” Vestberg said.

Verizon’s edge efforts are also be propelled by its push into private networks.

Joe Russo, EVP and president of global networks and technology at Verizon, told attendees at a different conference that the carrier’s network team can take advantage of those private network deployments to “put private MEC in those private network solutions” that are opening up multiple use cases.

IoT Analytics posits those top use cases include remote control of assets; facility connectivity and coverage; logistics automation using automated guided vehicles (AGVs) and automated mobile robots (AMRs); camera-based facility surveillance; and asset inspection.